New Special Issue of Stat: Statistical Consulting and Collaboration

We are delighted to present a new virtual special issue of Stat entitled Statistical Consulting and Collaboration.


Governments, organizations, businesses and individuals around the world collect data for making decisions, evaluating status and priorities, tracking progress, predicting future activities and for scientific research purposes. As the complexity and volume of data increase, technological advances increasingly focus on simplifying the collection of these data. However, care must be taken so that these simplification measures empower stakeholders to gain insight from data and do not result in inaccurate interpretations by researchers and decision makers.

The practicing statistician plays a unique and crucial role in scientific research and data science. They must delve deeply into the area of application and learn the terminology to understand and translate the conversations and questions into operational terms for statistical solution. It is the statistician who becomes the conduit into insightful understanding of risk and consequent inferential interpretation of the analytical results.

According to the ASA Section on Statistical Consulting, “Statistical consulting is the most challenging and most rewarding part of statistics. A consultant uses the art and science of statistics to solve a practical problem”. It is essential that statisticians continue to develop both the technical knowledge and collaborative skills to best assist and educate their collaborators and clients, yet, few resources for practicing statisticians exist.

This Special Issue on Statistical Consulting and Collaboration is intended to provide a forum for applied statisticians and data scientists to continue to learn from each other through implementations of cutting-edge methodology and examples of innovative problem solving, how to structure and assess successful collaborations, and, through evidence-based approaches, to develop skills as practicing statisticians. With this special issue the editors intend to provide insight into the entire Collaborative Process by including articles from experienced statistical consultants and collaborators. These authors have developed expertise in a) individual or group statistical consulting; b) organizing the structure of a consulting group; c) selecting and evaluating clients; d) joining an interdisciplinary study, or, e) successfully taking a study from initial contact to publication in a wide range of areas of application.

The authors’ papers are divided into three sections: Structuring and Assessing Collaborations, Skills for Statistical Consulting and Collaboration and Innovative Applications of Statistical Techniques. The latter section presents creative approaches used for emerging problems in applied statistics. Papers in this section highlight the crucial part the statistician plays in the Collaborative Process and the advances that were made possible by the use of standard statistical techniques in innovative ways. General approaches to specific problems are described, which have clear adaptation potential to similar problems in other fields.

In summary, this special issue will provide the reader with an overview of some of the real world experiences of consulting and collaborative statisticians and serve as a guide to important characteristics necessary for success.

Co-Editors Robyn L. Ball, Helen Zhang, H. Dean Johnson, Lee-Ann C. Hayak, Joe Rigdon, and Maggie Niu


Structuring and Assessing Collaborations

Gina-Maria Pomann, L. Ebony Boulware, Cliburn Chan, Steven C. Grambow Alexandra L. Hanlon, Megan L. Neely, Sarah B. Peskoe, Greg Samsa, Jesse D. Troy, Lexie Zidanyue Yang, Samantha M. Thomas. (2022). Experiential learning methods for biostatistics students: A model for embedding student interns in academic health centers (Open Access)
Erin T. Kaseda, Emily E. Graupman, Samuel Vincent, Reid Faith, Meghan M. Howe, Madison Dykins, Courtney N. Beussink, Aaminah Khan, Karolina Grotkowski, Steven A. Miller (2022). Statistical consulting in the healthcare professions: A model of student-led consulting services
Katrina L. Devick, Heather J. Gunn, Lori Lyn Price, Jareen K. Meinzen-Derr Felicity T. Enders, Susan M. Perkins, Phillip J. Schulte (2022). Collaborative biostatistics and epidemiology in academic medical centres: A survey to assess relationships with health researchers and ethical implications (Open Access)
Alexandra L. Hanlon, Alicia J. Lozano, Swathi Prakash, Emily B. Bezar, Walter T. Ambrosius, Guy Brock, Manisha Desai, Brad H. Pollock, Mary D. Sammel, Heidi Spratt, Leah J. Welty, Gina-Maria Pomann (2022). A comprehensive survey of collaborative biostatistics units in academic health centers (Open Access)

Skills for Statistical Consulting and Collaboration

C. Christina Mehta, Margaret R. Stedman, Sowmya R. Rao, Robert Podolsky (2022). Advice for isolated statisticians collaborating in academic healthcare centre settings
David Shilane, Nicole L. Lorenzetti, Nicole Di Crecchio, David K. Kreutter (2022). The virtual consulting company: Teaching statistical consulting through simulated experience
Ryan A. Peterson, Camille J. Hochheimer, Gary K. Grunwald, Rachel L. Johnson Cheyret Wood, Mary D. Sammel (2022). Reaping what you SOW: Guidelines and strategies for writing scopes of work for statistical consulting (Open Access)
George P. McCabe, John Newell (2022). The art of translational statistics (Open Access)
Kimberly A. Cressman, Julia L. Sharp (2022). Crafting statistical analysis plans: A cross-discipline approach

Emily H. Griffith, Julia L. Sharp, William C. Bridges, Bruce A. Craig, Kathryn J. Hanford, John R. Stevens (2022). The academic collaborative statistician: Research, training and evaluation (Open Access)

Eric A. Vance, Ilana M. Trumble, Jessica L. Alzen, Heather S. Smith (2022). Asking great questions

Innovative Applications of Statistical Techniques

Junwei Shen, Shirin Golchi, Erica EM Moodie, David Benrimoh (2022). Bayesian group sequential designs for cluster-randomized trials
Ariadna Garcia, Justin Lee, Vidhya Balasubramanian, Rebecca Gardner, Santosh E. Gummidipundi, Grace Hung, Todd Ferris, Lauren Cheung, Sumbul Desai Christopher B. Granger, Mellanie True Hills, Peter Kowey, Divya Nag, John S. Rumsfeld, Andrea M. Russo, Jeffrey W. Stein, Nisha Talati, David Tsay, Kenneth W. Mahaffey, Marco V. Perez, Mintu P. Turakhia, Haley Hedlin, Manisha Desaion behalf of the Apple Heart Study Investigators (2022). The development of a mobile app-focused deduplication strategy for the Apple Heart Study that informs recommendations for future digital trials  (Open Access)
Dillon T. Aberasturi, Walter W. Piegorsch, Edward J. Bedrick, Yves A. Lussier (2023). Accounting for extra-binomial variability with differentially expressed genetic pathway data: A collaborative bioinformatic study 
Ricardo Batista, Zhengyuan Zhu, David Peters, Kimberly Zarecor (2023). Predicting resident satisfaction with public schools in small town Iowa (Open Access)
Ming-Hui Chen, Daeyoung Lim, Nalini Ravishanker, Henry Linder, Mark Bolduc Brian McKeon Stanley Nolan (2022). Collaborative analysis for energy usage monitoring and management on a large university campus
Emily Slade, Anthony A. Mangino, Lara Daniels, Madison Liford, Dana Quesinberry (2023). Modelling overdose case fatality rates over time: The collaborative process 

Richard A. Levine, Patricia E. Rivera, Lingjun He, Juanjuan Fan, Marilee J. Bresciani Ludvick (2023). A learning analytics case study: On class sizes in undergraduate writing courses  (Open Access)